ODSC - Open Data Science

APRIL 23, 2025

Confluent Confluent provides a robust data streaming platform built around Apache Kafka. Amazon Web Services(AWS) AWS offers one of the most extensive AI and ML infrastructures in the world. Access Production-Grade Infrastructure Cloud providers such as AWS and Azure allow you to simulate real-world deployment scenarios.

Data Scientist 52

Data Scientist Azure Apache Kafka ML 52

Flipboard

NOVEMBER 21, 2023

In recent years, MathWorks has brought many product offerings into the cloud, especially on Amazon Web Services (AWS). Here is a quick guide on how to run MATLAB on AWS. Installation of AWS Command-Line Interface (AWS CLI) , AWS Configure , and Python3. Set up AWS Configure to interact with AWS resources.

Machine Learning 166

Machine Learning Machine Learning AWS Decision Trees 166

Pickl AI

MARCH 19, 2025

Python, SQL, and Apache Spark are essential for data engineering workflows. Real-time data processing with Apache Kafka enables faster decision-making. Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Common examples of time series data include sales revenue, system performance data (such as CPU utilization and memory usage), credit card transactions, sensor readings, and user activity analytics. It offers an AWS CloudFormation template for straightforward deployment in an AWS account.

AWS 118

AWS ML ML Apache Kafka 118

AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. To use this feature, you can write rules or analyzers and then turn on anomaly detection in AWS Glue ETL.

AWS 96

AWS ML ML Data Quality 96

AWS Machine Learning Blog

APRIL 19, 2023

Streaming ingestion – An Amazon Kinesis Data Analytics for Apache Flink application backed by Apache Kafka topics in Amazon Managed Streaming for Apache Kafka (MSK) (Amazon MSK) calculates aggregated features from a transaction stream, and an AWS Lambda function updates the online feature store.

ML 98

ML ML Apache Kafka SQL 98

AWS Machine Learning Blog

NOVEMBER 3, 2023

m How it’s implemented In our quest to accurately determine shot speed during live matches, we’ve implemented a cutting-edge solution using Amazon Managed Streaming for Apache Kafka (Amazon MSK). We’ve implemented an AWS Lambda function with the specific task of retrieving the calculated shot speed from the relevant Kafka topic.

AWS 128

AWS Apache Kafka Data Scientist Data Science 128

Data Science Dojo

JULY 24, 2023

Amazon S3: Amazon Simple Storage Service (S3) is a scalable object storage service provided by Amazon Web Services (AWS). It provides fault tolerance and high throughput for Big Data storage and processing. It allows organizations to store and retrieve any amount of data, making it popular for storing and managing Big Data in the cloud.

Big Data 195

Big Data Big Data Data Engineer Data Engineering 195

Women in Big Data

OCTOBER 9, 2024

After this, the data is analyzed, business logic is applied, and it is processed for further analytical tasks like visualization or machine learning. Data Ingestion: Data is collected and funneled into the pipeline using batch or real-time methods, leveraging tools like Apache Kafka, AWS Kinesis, or custom ETL scripts.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

AWS Machine Learning Blog

JANUARY 6, 2023

TR wanted to take advantage of AWS managed services where possible to simplify operations and reduce undifferentiated heavy lifting. TR used AWS Glue DataBrew and AWS Batch jobs to perform the extract, transform, and load (ETL) jobs in the ML pipelines, and SageMaker along with Amazon Personalize to tailor the recommendations.

AWS 98

AWS Data Warehouse ML ML 98

ODSC - Open Data Science

FEBRUARY 6, 2024

Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer. REGISTER NOW Data Orchestration and Workflow Management Apache Airflow Apache Airflow is renowned for its ability to build and schedule complex data pipelines.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 18, 2024

As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions. It utilises Amazon Web Services (AWS) as its main data lake, processing over 550 billion events daily—equivalent to approximately 1.3 petabytes of data.

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. However, you might be looking for a guide to help you understand the different types of Data Analytics projects you may undertake.

Analytics 40

Analytics Analytics Big Data Big Data 40

Pickl AI

JULY 25, 2024

This is essential for applications that demand immediate insights, such as fraud detection or real-time analytics. By centralising data from disparate sources, organisations can ensure that they have a unified view of their information, which is vital for analytics, reporting, and decision-making.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. Data privacy regulations will shape how organisations handle sensitive information in analytics. Continuous learning and adaptation will be essential for data professionals.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. OLAP (Online Analytical Processing): OLAP tools allow users to analyse data from multiple perspectives. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

DagsHub

OCTOBER 23, 2024

A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Tools and Techniques to Manage Unstructured Data Several tools are required to properly manage unstructured data, from storage to analytical tools. You also need the right technique to help manage unstructured data.

Machine Learning 52

Machine Learning Machine Learning AI Data Lakes 52

The MLOps Blog

MARCH 15, 2023

Data Consumption : You have reached a point where the data is ready for consumption for AI, BI & other analytics. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. The origins of a data pipeline connect it to the need for reusability and efficiency.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

The MLOps Blog

AUGUST 11, 2023

Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., As usage increased, the system had to be scaled vertically, approaching AWS instance-type limits. Today different stages exist within ML pipelines built to meet technical, industrial, and business requirements. 1 Data Ingestion (e.g.,

ML 52

ML ML Machine Learning Machine Learning 52

phData

MAY 15, 2025

This incredible capability is known as Real-Time Data Analytics , and it is revolutionizing the way we understand and utilize information. In this blog, we will uncover: What is real-time analytics, and why is it so important? How to implement a real-time analytics use case using AWS and Snowflake.

AWS 59

AWS Analytics Analytics Apache Kafka 59